Deep learning methods are a class of machine learning techniques capable of identifying highly complex patterns in large datasets. Here, we provide a perspective and primer on deep learning applications for genome analysis. We discuss successful applications in the fields of regulatory genomics, variant calling and pathogenicity scores. We include general guidance for how to effectively use deep learning methods as well as a practical guide to tools and resources. This primer is accompanied by an interactive online tutorial.

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We thank N. Wineinger, R. Dias, J. di Iulio and D. Evans for comments on the paper. The work of A. Telenti, A. Torkamani and P.M. is supported by the Qualcomm Foundation and the NIH Center for Translational Science Award (CTSA, grant UL1TR002550). Further support to A. Torkamani is from U54GM114833 and U24TR002306. J.Z. is supported by a Chan–Zuckerberg Biohub Investigator grant and National Science Foundation (NSF) grant CRII 1657155.

Author information


  1. Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA

    • James Zou
  2. Chan–Zuckerberg Biohub, San Francisco, CA, USA

    • James Zou
  3. Department of Electrical Engineering, Stanford University, Palo Alto, CA, USA

    • James Zou
    •  & Abubakar Abid
  4. Peltarion, Stockholm, Sweden

    • Mikael Huss
  5. Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden

    • Mikael Huss
  6. Scripps Research Translational Institute, La Jolla, CA, USA

    • Pejman Mohammadi
    • , Ali Torkamani
    •  & Amalio Telenti
  7. Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA

    • Pejman Mohammadi
    • , Ali Torkamani
    •  & Amalio Telenti


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All authors conceived and designed the project. J.Z., M.H., P.M., A. Torkamani and A. Telenti wrote the manuscript. J.Z. and A.A. wrote the online tutorial.

Competing interests

M.H. is an employee of Peltarion.

Corresponding authors

Correspondence to James Zou or Amalio Telenti.

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